Hybrid Modeling in Process Industries

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"This title introduces the underlying theory and demonstrates practical applications in different process industries using hybrid modeling. The fundamental part covers questions on ‶How to develop a hybrid model?”, ‶How to represent and identify unknown parts?”, ‶How to enhance the model quality by design of experiments?” and ‶How to compare different hybrid models?” together with tips and good practices for the efficient development of high quality hybrid models. The application part covers the utilization of hybrid modeling for typical process operation and design applications in industries such as chemical, petrochemical, biochemical, food and pharmaceutical process engineering."--Provided by publisher. Read more... Abstract: "This title introduces the underlying theory and demonstrates practical applications in different process industries using hybrid modeling. The fundamental part covers questions on ‶How to develop a hybrid model?”, ‶How to represent and identify unknown parts?”, ‶How to enhance the model quality by design of experiments?” and ‶How to compare different hybrid models?” together with tips and good practices for the efficient development of high quality hybrid models. The application part covers the utilization of hybrid modeling for typical process operation and design applications in industries such as chemical, petrochemical, biochemical, food and pharmaceutical process engineering."--Provided by publisher Content: Chapter 1: Benefits and challenges of hybrid modelling in the process industries: An introductionMoritz von Stosch, Jarka Glassey1.1 An intuitive introduction to hybrid modelling1.2 Key-properties and challenges of hybrid modelling1.3 Benefits and challenges of hybrid modelling in the process industries1.4 Hybrid modelling, the idea and its history 1.5 Setting the stageChapter 2: Hybrid Model Structures for Knowledge IntegrationMoritz von Stosch, Rui M.C. Portela, Rui Oliveira2.1. Introduction2.2. Hybrid semi-parametric model structures2.3. Examples 2.4. Concluding remarksChapter 3: Hybrid models and Experimental DesignMoritz von Stosch3.1. Introduction3.2. Design of Experiments (DoE)3.3. The Validity/Applicability Domain of hybrid models3.4. Hybrid model based (Optimal) Experimental Design3.5. ConclusionsChapter 4: Hybrid model identification and discrimination with practical examples from the chemical industrySchuppert and Th. Mrziglod4.1 Introduction4.2 Why data based modelling?4.3 Principles of data based modelling4.4 Structured hybrid modelling - introduction4.5. Practical realisation of Hybrid Models4.6 Applications4.7. SummaryChapter 5: Hybrid modeling of biochemical processesVytautas Galvanauskas and Rimvydas Simutis, Andreas Lubbert5.1 Introduction5.2 Hybrid modeling for process optimization5.3 Hybrid modeling for state estimation5.4 Hybrid modeling for control5.5 Hybrid modeling for fault analysis5.6 Concluding remarksChapter 6: Hybrid modelling of petrochemical processesVladimir Mahalec6.1 Introduction6.2 Computation of mass and energy balances6.3 Hybrid Models of petrochemical reactors6.4 Hybrid Models of Simple Distillation Towers6.5 Hybrid Models of Complex Distillation Towers6.6 Summaryã Chapter 7: Implementation of hybrid neural models to predict the behaviour of food transformation and food waste valorisation processesStefano Curcio7.1 Introduction7.2 Case study 1 - Convective drying of vegetables7.3. Case study 2 - Enzymatic transesterification of waste olive oil glycerides for biodiesel production7.4 ConclusionsChapter 8: Hybrid modelling of pharmaceutical processes and PATJarka Glassey8.1 Quality by Design and Process Analytical Technologies8.2 Case study8.3 Conclusions